No matter what line of work you are in, the odds are good that you’re going to be relying on data in order to get your job done. However, the idea of data can be confusing starting from the way you should store it to what data actually is. Furthermore, there are numerous types of data. One important example is discrete data and continuous data. Understanding the difference between discrete versus continuous types of data can make a big difference in your business, as it can enable you to understand when the use of certain types of data is appropriate. It can also help you better find appropriate tools to measure the difference between the two forms of data.
What is discrete data?
Discrete data is data that you are able to see and definitively define. It may involve positive integers or yes/no characteristics. Generally speaking, this makes discrete data relatively easy to define and measure. Discrete data can be seen and easily determined. This also means that it cannot occupy an infinite number of possibilities. Instead, it can occupy one of a series of numbers on a range.
Discrete data is set as a real number. This means that you will be able to easily determine and measure it. This includes:
- The color of an item.
- The number of people who have purchased a product.
- Salary levels or revenue that a business has generated.
- A stock price.
Key characteristics of discrete data
The most important thing to keep in mind when it comes to discrete data is that it cannot occupy an infinite number of possibilities. Discrete data is a number that involves a limited value. Let’s say you are measuring the revenue of a company. In theory, that measurement could be a trillion dollars, but such a measurement is still discrete data. This is because it could only occupy a set number of possibilities. This means it could be $1, $1.01, $1.02, etc. It could not be $1.024798.
Another way to think about discrete data is to think of it as data in which only certain values are possible. This means that discrete data only involves answering yes or no questions, such as “Does a product work?” The only possible answer is “yes” or “no,” and these are discrete answers.
What is continuous data?
Continuous data is data that occurs on an infinite scale. This means that it can occupy any point between two numbers.
Since continuous data is measured at any point, it is generally things such as measurements. For example:
- The width of a wall.
- The temperature of a room.
- The height or weight of a person.
- The time it takes to complete a task, such as finishing a race or completing a job.
Key characteristics of continuous data
The most important characteristic of continuous data is that it can occupy any number within a measurement. For example, let’s say you were trying to measure the temperature of a room. The temperature could be 74 degrees, 74.1, 74.11, 74.112, etc. This is because the temperature can occupy any number on your scale of measurement. This means that it is continuous data.
Why does this topic matter for small businesses?
This topic matters for small businesses because it may impact the way you measure data and use that data in the analysis.
Discrete data is generally easier to measure. This is because this data exists in an exact form. If you are dealing with revenue, your measurement comes from the currency. If you are dealing with people who purchased a product, you’ll be dealing with sales figures. As long as the method of recording the data is accurate, you can be confident in the data.
Continuous data can sometimes have qualities that make it seem similar to discrete data. The above example (the temperature of a room) is a perfect example of this. On most commonly used scales, the temperature of a room is usually determined in a whole number. However, the temperature could be any number. Only the lack of a completely accurate thermometer would keep you from determining the true temperature of a room. As a general rule, the accuracy of a method of measurement limits how accurate your continuous data will be.
From a small business perspective, you should be prepared to understand that these different forms of data require different methods of measurement. When you are measuring it, your data is likely going to be limited by your scale. If you have an accurate enough scale, you may be able to measure data using an extended series of numbers.
What action should a small-business owner take next?
The answer to this question depends on your specific line of work. However, a small-business owner is well-served by understanding the difference between the two numbers. If you know data is continuous, you will know that the measurement you make will not be 100% reflective of the “true” measurement of an item, and it will be limited by the method of measurement you make. As such, a small-business owner must be prepared to measure continuous data as best they can while also understanding that their measurement will have limits. If working with discrete data, a small-business owner must understand that there is no scale-related reason that their data should be limited.
Note: The applications mentioned in this article are examples to show a feature in context and are not intended as endorsements or recommendations. They have been obtained from sources believed to be reliable at the time of publication.